Concept

Smoothing

Related publications (39)

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Stability: a search for structure

Wouter Jongeneel

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

EPFL2024

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Olga Fink, Tianfu Li

Intelligent fault diagnosis has been increasingly improved with the evolution of deep learning (DL) approaches. Recently, the emerging graph neural networks (GNNs) have also been introduced in the field of fault diagnosis with the goal to make better use o ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Functional data analysis with rough sample paths?

Victor Panaretos, Neda Mohammadi Jouzdani

Functional data are typically modeled as sample paths of smooth stochastic processes in order to mitigate the fact that they are often observed discretely and noisily, occasionally irregularly and sparsely. The smoothness assumption is imposed to allow for ...

TAYLOR & FRANCIS LTD2023

Inference and Computation for Sparsely Sampled Random Surfaces

Victor Panaretos, Tomas Rubin, Tomas Masák

Nonparametric inference for functional data over two-dimensional domains entails additional computational and statistical challenges, compared to the one-dimensional case. Separability of the covariance is commonly assumed to address these issues in the de ...

TAYLOR & FRANCIS INC2022

Testing For The Rank Of A Covariance Operator

Victor Panaretos

How can we discern whether the covariance operator of a stochastic pro-cess is of reduced rank, and if so, what its precise rank is? And how can we do so at a given level of confidence? This question is central to a great deal of methods for functional dat ...

INST MATHEMATICAL STATISTICS-IMS2022

Some first results on the consistency of spatial regression with partial differential equation regularization

Fabio Nobile, Eleonora Arnone

We study the consistency of the estimator in spatial regression with partial differential equa-tion (PDE) regularization. This new smoothing technique allows to accurately estimate spatial fields over complex two-dimensional domains, starting from noisy ob ...

2020

Functional lagged regression with sparse noisy observations

Victor Panaretos, Tomas Rubin

A functional (lagged) time series regression model involves the regression of scalar response time series on a time series of regressors that consists of a sequence of random functions. In practice, the underlying regressor curve time series are not always ...

WILEY2020

Automatic L2 Regularization for Multiple Generalized Additive Models

Yousra El Bachir

Multiple generalized additive models are a class of statistical regression models wherein parameters of probability distributions incorporate information through additive smooth functions of predictors. The functions are represented by basis function expan ...

EPFL2019

Robust and adaptive approaches for Relative Geologic Time Estimation

Mireille El Gheche

For a geoscientist, the Relative Geologic Time (RGT) is an important tool to perform chronostratigraphic analysis. However, automatically estimate an RGT image from a seismic image can be a challenging task where we have to respect seismic features, the de ...

ELSEVIER SCIENCE BV2018

Learning Laplacian Matrix in Smooth Graph Signal Representations

Pascal Frossard, Pierre Vandergheynst, Xiaowen Dong

The construction of a meaningful graph plays a crucial role in the success of many graph-based representations and algorithms for handling structured data, especially in the emerging field of graph signal processing. However, a meaningful graph is not alwa ...

Institute of Electrical and Electronics Engineers2016